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A Python package to mix-and-match conflicting clustering results in single cell analysis, and generate reconciled clustering solutions.

Project description

scTriangulate

scTriangulate is a Python package to mix-and-match conflicting clustering results in single cell analysis, and generate reconciled clustering solutions.

Tutorials

Check our full documentation.

Overview

schema

It can potentially be used in an array of settings:

  1. Running same unsupervised clustering (i.e. Leiden) algorithm using different resolutions.

  2. Running unsupervised clustering using different algorithms.

  3. Running reference mapping tools using different reference atlases.

  4. Clustering labels from matched multi-modalities (RNA, ADT, ATAC, etc)

schuma_chop

Citation

scTriangulate will be presented in 2021 CZI Single-Cell Biology Annual Meeting.

A preprint will come out soon.

Contact

Guangyuan(Frank) Li

li2g2@mail.uc.edu

PhD student, Biomedical Informatics

Cincinnati Children’s Hospital Medical Center(CCHMC)

University of Cincinnati, College of Medicine

Project details


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